Stroke is one of the leading causes of long-term disability worldwide, with motor impairments being among the most common and debilitating consequences [1, 2]. Post-stroke motor dysfunction significantly limits patients’ independence and quality of life, posing a major burden on healthcare systems and caregivers [3]. Despite advances in acute stroke management and rehabilitation techniques, many survivors experience incomplete motor recovery, highlighting the need for adjunctive therapies that can enhance neurorehabilitation outcomes [4].

In recent years, attention has turned to pharmacological agents that may promote neural repair and plasticity. One such agent is fluoxetine, a selective serotonin reuptake inhibitor (SSRI) traditionally used as an antidepressant [5]. Preclinical studies and early clinical trials have suggested that fluoxetine may enhance motor recovery after stroke by modulating neuroplasticity, increasing neurogenesis, and improving synaptic connectivity [6, 7]. The FLAME trial (2011) was one of the first randomized controlled trials (RCTs) to report a significant improvement in motor function with fluoxetine in stroke patients, independent of its antidepressant effects [8].

However, subsequent trials have produced mixed results regarding both the efficacy and safety of fluoxetine in post-stroke rehabilitation [9–11]. Concerns have emerged over adverse effects such as bone fractures, seizures, and hyponatremia, particularly in older adults [12, 13]. Moreover, differences in study designs, populations, and treatment durations have led to uncertainty about its routine clinical use [14].

Given these inconsistencies, a comprehensive synthesis of current evidence is needed to guide clinical decision-making. This systematic review and meta-analysis aims to evaluate the efficacy and safety of fluoxetine in improving motor recovery and health-related quality of life (HRQoL) in post-stroke patients, and to identify optimal treatment parameters for its potential use in stroke rehabilitation.

This systematic review and meta-analysis was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and registered in PROSPERO (ID: CRD420251011077). Institutional Review Board (IRB) approval was not required because this study did not involve direct human participants or identifiable personal data; therefore, ethical compliance with human or animal studies was not applicable.

A single reviewer (INW) conducted a comprehensive search of the Google Scholar, PubMed, and Scopus databases, covering all articles published from database inception up to March 2025. The search strategy included the following terms: (“Fluoxetine”) AND (“Motor Recovery”) AND (“Stroke”) AND (“Randomized Controlled Trial” OR “RCT” OR “FLAME Trial”). The search was restricted to studies evaluating the efficacy and safety of fluoxetine in improving motor recovery and HRQoL in post-stroke patients.

The inclusion criteria for this study were defined as follows: adults aged 18 years and older diagnosed with acute or chronic stroke; patients treated with fluoxetine compared to placebo; studies designed as RCTs, clinical trials, or randomized trials comparing fluoxetine with placebo in post-stroke populations; and studies reporting follow-up data on motor recovery, HRQoL, and treatment-related adverse events. Studies were excluded if they were reviews, case reports, or non-original research articles; lacked a placebo comparison group; or did not report outcomes related to motor recovery, HRQoL, or adverse events. Two authors (INW and INGNY) independently screened titles and abstracts using Microsoft Excel software. Any discrepancies in the selection process were resolved through discussion with a third investigator (IGAAPAY) to reach consensus.

To evaluate the methodological quality of the included trials, the risk of bias was assessed at the study using the Cochrane Risk of Bias 2 (ROB-2) tool for RCTs. Two independent reviewers (INW and KDKK) screened all articles and independently rated the following domains: bias arising from the randomization process, bias due to deviations from intended interventions, bias due to missing outcome data, bias in measurement of the outcome, and bias in selection of the reported results. Each domain was classified as having a “low risk,” “some concerns,” or “high risk” of bias. Any discrepancies in data extraction or quality assessment were resolved through discussion until consensus was reached.

Two independent authors (INW and IGAAPAY) conducted the data extraction process. A standardized data collection form was used to systematically extract key information from each trial, including the first author, year of publication, study location, sample size, patient diagnosis, study design, outcome measures, and measurement tools. Additionally, detailed information regarding the treatment protocols was recorded, including the intervention and control regimens, duration of treatment, and primary results.

The primary outcome of this study was motor recovery in post-stroke patients, assessed using a range of validated motor function measures. These included the Fugl–Meyer Motor Scale (FMMS), National Institutes of Health Stroke Scale (NIHSS), Rivermead Mobility Index (RMI), modified Rankin Scale (mRS), Vogel-Meyer Motor Scale, pinch strength measured with a dynamometer, number of finger tapping movements, Saltin-Grimby Physical Activity Level Scale (SGPALS), Timed Hand Function Test (THF), and upper extremity changes in the Fugl-Meyer Assessment (FMA-UE). Secondary outcomes included: i) HRQoL, evaluated using various instruments such as the Mental Health Inventory-5 (MHI-5), Barthel Index, Montgomery–Asberg Depression Rating Scale (MADRS), EuroQol 5 Dimensions 5 Levels (EQ-5D-5L), and Patient Health Questionnaire-9 (PHQ-9); 2) incidence of treatment-related adverse events, including bone fractures, seizures, hyperglycemia, hyponatremia, bleeding events, and all-cause mortality.

We conducted statistical analyses to evaluate the study outcomes. Motor recovery in post-stroke patients was analyzed based on treatment duration and optimal dosage, using the standardized mean difference (SMD) with a 95% confidence interval (CI), due to the variation in tools used to assess motor function. HRQoL outcomes were also assessed using SMD with 95% CI. For dichotomous outcomes, such as treatment-related adverse events, odds ratios (ORs) with 95% CIs were calculated. Heterogeneity among studies was assessed using the I² statistic, with values of 25%, 50%, and 75% indicating low, moderate, and high heterogeneity, respectively. A P value of ≤ 0.05 was considered statistically significant for heterogeneity. In the presence of significant heterogeneity, a random-effects model was applied for meta-analysis; otherwise, a fixed-effects model was used. All statistical analyses were performed using Review Manager (RevMan) version 5.1.0 (The Cochrane Collaboration, UK).

A total of 1,173 potential research articles were initially identified. After removing duplicates, screening titles and abstracts, reviewing full texts, and applying the inclusion and exclusion criteria, 23 eligible studies were included in the systematic review and meta-analysis (Fig. 1).

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Figure 1. PRISMA flow diagram of study selection process for the systematic review and meta-analysis. PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

The quality of the included RCTs was evaluated using the Cochrane ROB-2 tool. Among the 23 included studies, six were identified as having “some concerns” regarding risk of bias, while one study was assessed as having a “high risk” of bias (Fig. 2). Babul et al (2017) [15] demonstrated some concerns due to insufficient reporting of the randomization process and blinding procedures. Although appropriate outcome measures were utilized and an intention-to-treat (ITT) analysis was conducted, missing data were imputed using mean substitution without adequate sensitivity analyses, potentially introducing bias. Dehghani et al (2024) [16] raised concerns primarily due to incomplete reporting on trial completion and missing data handling. The study did not clarify whether all enrolled participants completed the intervention, nor did it describe methods for addressing missing data, which may have introduced attrition bias. The study by Dike et al (2019) [17] was a single-blind trial that did not clearly specify whether participants or outcome assessors were blinded. Additionally, the lack of a placebo in the control group and the potential for unblinded outcome assessment posed a risk of detection and performance biases, especially given the reliance on subjective functional measures such as the FMMS and the mRS. The study by Guo et al (2016) [18] was limited by the absence of blinding among participants and clinicians, as well as by allowing re-randomization during the trial. Furthermore, the methods for handling missing data were not reported, increasing the potential for performance and attrition biases. He et al (2016) [19] exhibited some concerns due to lack of blinding in both patients and clinical staff, which may have influenced participants’ behavior and clinicians’ assessments. The study also did not provide sufficient details regarding allocation concealment, raising the possibility of selection bias. The study by Krishnan et al (2021) [20] lacked blinding in both participants and outcome assessors, which introduces a high risk of performance and detection bias. This is particularly significant given the use of subjective or semi-subjective outcome measures such as motor function scales. The study by Saadat et al (2025) [21] was rated as having a high risk of bias. This was attributed to the absence of transparency in the randomization process, unblinded outcome assessment, and the lack of a pre-registered protocol. These methodological shortcomings increase the likelihood of selective outcome reporting and exaggerated effect estimates.

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Figure 2. Risk of bias assessment of included studies using the Cochrane Risk of Bias 2 (ROB-2) tool.

A comprehensive overview included a total of 23 RCTs involving 12,041 post-stroke patients, with publication dates ranging from 2009 to 2025. Sample sizes varied across studies, from 10 to 3,127 participants. Detailed descriptions of the interventions used in each trial are provided in Tables 1 and 2 [8, 15–36].

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Table 1. Characteristics of Included Studies in the Systematic Review and Meta-Analysis

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Table 2. Treatment Regimens Administered in Included Studies

Sixteen studies were included in the analysis comparing the effects of fluoxetine versus placebo on motor recovery, categorized by optimal dose (Fig. 3) and treatment duration (Fig. 4). Due to significant heterogeneity among studies (I² = 96%), SMDs were pooled using a random-effects model. The analysis demonstrated a significant improvement in motor recovery for the fluoxetine group with a treatment duration of 90 days (3 months) (SMD = 0.82; 95% CI, 0.23–1.42; P = 0.006) and an optimal daily dose of 20 mg (SMD = 0.36; 95% CI, 0.00–0.71; P = 0.05).

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Figure 3. Comparison of fluoxetine dosages in relation to motor recovery outcomes. SD: standard deviation; CI: confidence interval.

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Figure 4. Effect of fluoxetine treatment duration on motor recovery in post-stroke patients. SD: standard deviation; CI: confidence interval.

A total of 17 studies were included in the analysis comparing HRQoL between the fluoxetine and placebo groups (Fig. 5). Due to substantial heterogeneity among the studies (I² = 98%), SMDs were pooled using a random-effects model. The results demonstrated a statistically significant improvement in HRQoL in the fluoxetine group compared to the placebo group (SMD = 0.37; 95% CI, 0.13–0.60; P = 0.002).

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Figure 5. Effect of fluoxetine on health-related quality of life in post-stroke patients. SD: standard deviation; CI: confidence interval.

A total of eight studies were included in the analysis comparing the incidence of new treatment-related adverse events between the fluoxetine and placebo groups (Fig. 6). Based on the heterogeneity test results (I² = 56.5%), ORs were pooled using a fixed-effect model. The analysis indicated that the fluoxetine group had a significantly higher risk of new adverse events compared to the placebo group (OR = 1.55; 95% CI, 1.33–1.80; P < 0.001), particularly bone fractures (OR = 2.30; 95% CI, 1.65–3.20; P < 0.001), seizures (OR = 1.48; 95% CI, 1.11–1.99; P = 0.009), and hyponatremia (OR = 2.11; 95% CI, 1.22–3.66; P = 0.007).

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Figure 6. Incidence of new adverse events related to fluoxetine treatment in post-stroke patients. CI: confidence interval.

To assess the presence of publication bias in the meta-analysis of motor recovery, HRQoL, and new incidence of adverse events related to treatment, the “metabias” function from Review Manager 5.1.0 (Cochrane, UK) was utilized. Upon examination of the funnel plot, it is evident that the distribution of studies on both the left and right sides of the plot is equal, suggesting a symmetrical distribution and no indication of publication bias (Fig.7).

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Figure 7. Publication bias was assessed using funnel plots for each outcome, including (a) duration of treatment on motor recovery, (b) dosage of treatment on motor recovery, (c) health-related quality of life, and (d) treatment-related adverse events. MHI-5: Mental Health Inventory-5; MADRS: Montgomery–Asberg Depression Rating Scale; EQ-5D-5L: EuroQol 5 Dimensions 5 Levels; PHQ-9: Patient Health Questionnaire-9.

The results of this analysis demonstrate that fluoxetine significantly improves motor recovery when administered at a daily dose of 20 mg for a duration of 3 months (90 days) and also enhances HRQoL. However, fluoxetine is associated with a significant increase in treatment-related adverse events, including bone fractures, seizures, and hyponatremia. These findings suggest that while fluoxetine offers benefits in motor recovery and quality of life, careful consideration must be given to the dosage, duration of treatment, and thorough screening for risk factors to minimize potential side effects.

Our findings align with those of Liu et al (2021) [37], who reported that fluoxetine may improve motor recovery but does not significantly enhance overall functional recovery. Similarly, Mead et al (2020) [38] found that fluoxetine is associated with better neurological and depression scores, as well as fewer diagnoses of depression, but observed no significant difference in the proportion of patients achieving independence or disability outcomes, while noting an increased risk of seizures. Earlier meta-analyses by Yi et al (2010) [39], Gu et al (2018) [40], and Mead et al (2012) [41] suggested that fluoxetine might reduce dependency and disability if administered early after stroke.

Importantly, the significant associations observed for seizures and hyponatremia were largely driven by a limited number of large-scale trials, particularly Hankey et al (2020) [22] and Lundstrom et al (2020) [23], which contributed the highest statistical weight in the pooled analysis. Although the pooled results demonstrated statistical significance, the relatively small number of studies reporting these specific adverse events warrants cautious interpretation. The heavy influence of a few large multicenter trials may have disproportionately shaped the pooled estimates. Therefore, these findings should be confirmed in future well-powered randomized trials specifically designed to evaluate safety outcomes.

Fluoxetine, primarily indicated for the treatment of depression and other psychiatric disorders, has recently garnered interest for its potential efficacy in promoting motor recovery post-stroke. Preclinical investigations in animal models have elucidated several mechanistic pathways, through which fluoxetine may exert neurorestorative effects [24, 25]. Notably, fluoxetine, as a SSRI, enhances neurogenesis within canonical neurogenic regions such as the hippocampus and the subventricular zone [26–28]. This effect is mediated, in part, by the upregulation of neurotrophic factors, which are critical for neuronal survival, synaptic plasticity, and the reorganization of neural circuits following ischemic injury [29–32, 42].

Moreover, fluoxetine exhibits anti-inflammatory properties by attenuating microglial activation and neutrophil infiltration, thereby reducing the release of pro-inflammatory cytokines that exacerbate neuronal injury [33–35]. This immunomodulatory capacity may contribute to the preservation of neural tissue and facilitate functional recovery. Additionally, fluoxetine appears to influence cerebrovascular regulation via the induction of heme oxygenase-1 (HO-1) and hypoxia-inducible factor-1 alpha (HIF-1α), proteins implicated in vascular homeostasis and adaptation to ischemic stress [36, 43]. The upregulation of β-1 adrenergic receptors observed in ischemic brain regions following SSRI treatment further suggests a potential role in enhancing neural repair processes, although the precise molecular mechanisms warrant further elucidation [44, 45].

Despite these compelling findings from animal studies, the clinical applicability of these mechanisms in human stroke patients remains to be conclusively demonstrated. The RCTs analyzed herein did not assess neurogenic or regenerative endpoints directly, likely due to the protracted timeline required for such processes and the relatively short duration of follow-up. While our meta-analysis supports the therapeutic benefits of fluoxetine in improving motor function and HRQoL, it concurrently underscores an increased incidence of adverse events, notably bone fractures, seizures, and hyponatremia. These safety concerns necessitate vigilant risk assessment and monitoring during clinical use.

Given the elevated risk of bone fractures associated with fluoxetine use, adjunctive strategies such as vitamin D supplementation may be considered to mitigate this adverse effect. Vitamin D plays a pivotal role in calcium homeostasis and bone metabolism, and its supplementation has been shown to reduce fracture risk in at-risk populations. Similarly, to address the increased incidence of seizures and hyponatremia, comprehensive monitoring of electrolyte levels and neurological status is essential. The potential role of adjunctive strategies, such as magnesium supplementation or seizure prophylaxis, remains uncertain and may warrant investigation in future studies, as current evidence is insufficient to support routine clinical implementation, although current evidence remains limited and warrants further clinical investigation.

Although preclinical evidence provides a robust biological rationale supporting fluoxetine’s neurorestorative potential, further rigorous clinical investigations are essential to validate these mechanisms in human populations, optimize dosing regimens, and balance therapeutic efficacy against patient safety. The incorporation of adjunctive interventions, such as vitamin D supplementation and careful electrolyte management, may mitigate adverse events and improve the overall safety profile of fluoxetine in post-stroke rehabilitation.

Despite these promising findings, this meta-analysis is subject to several important limitations that warrant careful consideration. A primary contributor to heterogeneity is the considerable variation in assessment tools employed to measure motor recovery across included studies. While some trials utilized comprehensive and validated instruments like the FMMS, others relied on alternative measures such as the NIHSS, RMI, or finger tapping counts. These instruments differ markedly in sensitivity, scope, and focus, which likely contributed to the moderate to high heterogeneity observed in the primary outcomes (I² = 96%), thereby limiting direct comparability and generalizability of results. Moreover, variability in study design, sample size, and patient demographic characteristics may have further amplified this heterogeneity.

Although fluoxetine demonstrated statistically significant improvements in motor recovery and HRQoL, the associated increase in treatment-related adverse events including bone fractures, seizures, and hyponatremia raises critical safety concerns that may restrict its broad clinical applicability. Additional heterogeneity arose from differences in treatment duration, dosage regimens, follow-up periods, and outcome assessment methodologies, further complicating the interpretation and external validity of the findings.

To contextualize the observed safety signals, it is important to consider whether these adverse events are specific to the post-stroke population or represent established pharmacological effects of fluoxetine. In psychiatric populations, SSRIs, including fluoxetine, have been associated with an increased risk of falls, bone fractures, hyponatremia, and, in rare cases, seizures. Several large observational studies in patients treated for depression have demonstrated a higher incidence of fracture and fall-related injuries, potentially mediated by SSRI-induced reductions in bone mineral density, impaired platelet function, or effects on balance and psychomotor performance [45–48].

These findings suggest that at least part of the increased risk observed in our meta-analysis may reflect class-related adverse effects rather than stroke-specific mechanisms alone. However, patients recovering from stroke may be particularly vulnerable due to pre-existing motor impairment, frailty, advanced age, and polypharmacy. Such factors could amplify the baseline pharmacological risks associated with fluoxetine, thereby contributing to the higher incidence of adverse outcomes observed in this population. Distinguishing between drug-intrinsic effects and stroke-related susceptibility remains challenging and warrants further investigation through comparative safety analyses across different patient populations.

Demographic characteristics represent an important yet underexplored factor in the interpretation of safety outcomes. The observed increase in bone fracture risk, for instance, may carry differential clinical implications across patient subgroups, particularly among postmenopausal women, who have a higher baseline prevalence of osteoporosis. However, most included trials did not consistently report stratified analyses by sex or age, thereby limiting our ability to evaluate potential effect modification across demographic subgroups. The absence of detailed demographic reporting restricts meaningful risk stratification and may obscure clinically relevant heterogeneity in treatment response and adverse event susceptibility.

Similarly, prior exposure to fluoxetine or other SSRIs represents a potentially influential yet insufficiently documented variable. The majority of included trials did not specify whether participants were fluoxetine-naive at the time of enrollment. Previous antidepressant exposure may plausibly influence both therapeutic responsiveness and tolerability through alterations in neuroplasticity pathways or receptor sensitivity, thereby affecting clinical outcomes following stroke. Future investigations should explicitly document and stratify patients according to prior SSRI exposure to clarify its role in modulating recovery trajectories.

Taken together, these considerations underscore the need for rigorously designed, adequately powered multicenter RCTs employing standardized outcome measures and comprehensive baseline characterization. Future studies should extend follow-up beyond the commonly evaluated 90-day treatment window, delineate patient subpopulations most likely to derive net clinical benefit, and directly compare fluoxetine with alternative pharmacological and non-pharmacological rehabilitation strategies. In parallel, mechanistic studies incorporating advanced neuroimaging or biomarker analyses may further elucidate the biological substrates underlying observed clinical effects. Such efforts are essential to refining clinical guidelines and optimizing the risk-benefit profile of fluoxetine in post-stroke rehabilitation.

This systematic review and meta-analysis demonstrates that fluoxetine, administered at a dose of 20 mg/day for 90 days, may significantly enhance motor recovery and improve HRQoL in post-stroke patients. However, these therapeutic benefits are tempered by an increased risk of serious adverse events, notably bone fractures, seizures, and hyponatremia. Given these safety concerns and variability among studies, fluoxetine should be prescribed with caution, limited to carefully selected patients under vigilant clinical supervision. To mitigate the risk of adverse events, adjunctive strategies such as vitamin D supplementation to reduce fracture risk, along with appropriate electrolyte monitoring and seizure prophylaxis, should be considered. Future high-quality, large-scale RCTs are warranted to further elucidate the long-term safety profile of fluoxetine, identify patient subgroups most likely to benefit, and compare its efficacy with alternative rehabilitation interventions, thereby guiding evidence-based clinical practice.

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